The amount of information contained in documents is rapidly increasing. There are many industries such as law, education, journalism, politics, economics, etc. that may benefit from rapid and low-cost document analysis. The cost and relatively slow speed of manual, human analysis makes it effectively impossible or impracticable to perform document analysis at the scale, speed, and cost desired in many industries. “Offshoring” to take advantage of lower costs may allow the hiring of a larger number of people to analyze documents at a lower price per hour of labor. Even so, there is a lower bound on costs and an upper bound on throughput. Using multiple different people to provide manual analysis also has a strong potential to introduce inconsistencies because of variation in different individuals' subjective judgment. For example, analyzing a corpus of a million 30-page text documents overnight would be impossible using only human analysis. Automated document analysis using computers is much quicker than human analysis and performs at much lower cost. Additionally, automated document analysis provides for consistent and objective analysis that reduces discrepancies seen with subjective, error-prone human analysis. Further, human analysis is often difficult and impractical when analyzing documents in different languages. In order to analyze documents in a large number of languages, large amounts of humans which speak different languages and are trained to analyze the documents are required. Thus, devices and methods that can analyze documents in a way that emulates human analysis, and are applicable to a large number of languages, will have broad application across many different industries.